This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LTVRE_ROB98.40 199.67 399.71 299.56 1899.85 1899.11 4299.90 199.78 599.63 1299.78 1099.67 2199.48 699.81 14299.30 3199.97 2399.77 16
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
3Dnovator98.27 298.81 6898.73 6799.05 10398.76 24397.81 13899.25 3299.30 13898.57 10398.55 18099.33 7297.95 7399.90 4797.16 13499.67 14999.44 135
3Dnovator+97.89 398.69 8798.51 9799.24 7898.81 23998.40 8899.02 5499.19 17098.99 7598.07 20399.28 7597.11 12799.84 10396.84 15299.32 21399.47 125
DeepC-MVS97.60 498.97 5498.93 5199.10 9399.35 12597.98 11998.01 15099.46 8297.56 16299.54 3599.50 4698.97 1899.84 10398.06 9399.92 4999.49 111
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS96.93 598.32 13898.01 15899.23 7998.39 28698.97 5195.03 32299.18 17496.88 20999.33 7298.78 17398.16 5799.28 33096.74 15899.62 15799.44 135
DeepC-MVS_fast96.85 698.30 14098.15 14498.75 14598.61 26897.23 16697.76 17499.09 19397.31 18698.75 15998.66 19097.56 9199.64 26196.10 20099.55 18399.39 151
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVScopyleft96.65 797.09 22696.68 23198.32 20398.32 29097.16 17398.86 7199.37 10789.48 33396.29 30399.15 10296.56 16499.90 4792.90 28399.20 22997.89 292
ACMH96.65 799.25 3099.24 3599.26 7699.72 3398.38 9099.07 5299.55 5498.30 11599.65 2399.45 5699.22 1099.76 19998.44 7699.77 10599.64 40
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+96.62 999.08 4299.00 4999.33 6799.71 3498.83 5798.60 8399.58 3699.11 6199.53 3799.18 9298.81 2399.67 24696.71 16399.77 10599.50 104
COLMAP_ROBcopyleft96.50 1098.99 4998.85 5499.41 5399.58 5799.10 4398.74 7599.56 4999.09 6899.33 7299.19 9098.40 4399.72 22895.98 20499.76 11499.42 143
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS96.21 1196.63 24695.95 25398.65 15498.93 21198.09 10596.93 23899.28 14283.58 34898.13 20097.78 26496.13 18199.40 31493.52 27299.29 21998.45 275
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM96.08 1298.91 5998.73 6799.48 4599.55 7399.14 3598.07 13699.37 10797.62 15499.04 11898.96 14298.84 2199.79 17497.43 12599.65 15499.49 111
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS95.94 1395.90 26195.35 26697.55 24797.95 30694.79 24998.81 7496.94 30392.28 30995.17 32898.57 20789.90 27999.75 20591.20 31397.33 32398.10 287
OpenMVS_ROBcopyleft95.38 1495.84 26395.18 27297.81 23198.41 28597.15 17497.37 21098.62 26083.86 34798.65 16498.37 22694.29 24099.68 24088.41 32798.62 27696.60 332
ACMP95.32 1598.41 13098.09 15199.36 5799.51 8498.79 6097.68 18199.38 10395.76 24998.81 15498.82 16898.36 4599.82 12994.75 23599.77 10599.48 117
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLCcopyleft94.65 1696.51 25095.73 25698.85 13098.75 24497.91 12696.42 26999.06 19690.94 32595.59 31697.38 28894.41 23799.59 27590.93 31698.04 30999.05 223
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet93.40 1795.67 26595.70 25795.57 31198.83 23488.57 32692.50 34597.72 28692.69 30396.49 30096.44 30893.72 25399.43 31293.61 26999.28 22098.71 262
PCF-MVS92.86 1894.36 29593.00 31398.42 19298.70 25397.56 15393.16 34399.11 19179.59 35197.55 24797.43 28592.19 26899.73 21979.85 35199.45 19997.97 291
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS91.63 1992.24 32290.90 32596.27 28897.22 33391.24 31994.36 33393.33 33992.37 30792.24 34694.58 34466.20 35899.89 5693.16 27994.63 34497.66 305
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
PMVScopyleft91.26 2097.86 17597.94 16397.65 24099.71 3497.94 12598.52 9198.68 25698.99 7597.52 25099.35 6897.41 10498.18 35091.59 30499.67 14996.82 329
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_089.98 2191.15 32790.30 32793.70 33197.72 31384.34 34890.24 34997.42 29090.20 33093.79 34293.09 35190.90 27598.89 34586.57 33372.76 35497.87 294
MVEpermissive83.40 2292.50 31991.92 32194.25 32598.83 23491.64 30592.71 34483.52 35795.92 24686.46 35595.46 32895.20 21495.40 35480.51 35098.64 27495.73 342
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary75.91 2396.29 25595.44 26498.84 13196.25 34798.69 6797.02 23399.12 18988.90 33697.83 22298.86 16089.51 28198.90 34491.92 29799.51 19198.92 239
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ppachtmachnet_test97.50 19797.74 17596.78 27698.70 25391.23 32094.55 33199.05 20096.36 22999.21 9598.79 17296.39 17399.78 18496.74 15899.82 8299.34 170
SMA-MVS98.47 12498.11 14899.53 3299.16 16799.27 1698.05 14099.30 13894.34 28499.22 9499.10 10997.72 8299.79 17496.45 18399.68 14399.53 91
tfpn11194.33 29693.78 30095.96 30199.06 18591.35 31498.03 14294.24 33298.33 11197.40 25994.98 33679.84 32999.68 24083.94 34298.22 29096.86 325
conf0.0194.82 28494.07 29097.06 26499.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29796.86 325
GSMVS98.81 251
test_part397.25 21796.66 22098.71 18199.86 7793.00 281
conf0.00294.82 28494.07 29097.06 26499.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29796.86 325
thresconf0.0294.70 28894.07 29096.58 27999.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29795.42 344
tfpn_n40094.70 28894.07 29096.58 27999.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29795.42 344
tfpnconf94.70 28894.07 29096.58 27999.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29795.42 344
tfpnview1194.70 28894.07 29096.58 27999.21 15094.53 25798.47 10392.69 34095.61 25197.81 22595.54 32177.71 34199.80 15491.49 30698.11 29795.42 344
tfpn100094.81 28694.25 28996.47 28699.01 19993.47 28798.56 8792.30 34996.17 23697.90 21296.29 31076.70 34799.77 19493.02 28098.29 28696.16 336
test_part299.36 12199.10 4399.05 115
tfpn_ndepth94.12 30393.51 30795.94 30298.86 22693.60 28698.16 12791.90 35194.66 27597.41 25895.24 33176.24 34899.73 21991.21 31297.88 31294.50 349
test_part199.28 14297.56 9199.57 17499.53 91
conf200view1194.24 29993.67 30495.94 30299.06 18591.35 31498.03 14294.24 33298.33 11197.40 25994.98 33679.84 32999.62 26483.05 34498.08 30596.86 325
thres100view90094.19 30093.67 30495.75 30799.06 18591.35 31498.03 14294.24 33298.33 11197.40 25994.98 33679.84 32999.62 26483.05 34498.08 30596.29 333
tfpnnormal98.90 6098.90 5298.91 12299.67 4497.82 13699.00 5999.44 8899.45 2999.51 4399.24 8298.20 5599.86 7795.92 20699.69 13899.04 224
tfpn200view994.03 30593.44 30895.78 30698.93 21191.44 30897.60 19394.29 33097.94 12897.10 27094.31 34579.67 33399.62 26483.05 34498.08 30596.29 333
view60094.87 27994.41 28196.26 28999.22 14491.37 31098.49 9794.45 32598.75 8997.85 21795.98 31480.38 32499.75 20586.06 33598.49 28097.66 305
view80094.87 27994.41 28196.26 28999.22 14491.37 31098.49 9794.45 32598.75 8997.85 21795.98 31480.38 32499.75 20586.06 33598.49 28097.66 305
conf0.05thres100094.87 27994.41 28196.26 28999.22 14491.37 31098.49 9794.45 32598.75 8997.85 21795.98 31480.38 32499.75 20586.06 33598.49 28097.66 305
tfpn94.87 27994.41 28196.26 28999.22 14491.37 31098.49 9794.45 32598.75 8997.85 21795.98 31480.38 32499.75 20586.06 33598.49 28097.66 305
ESAPD98.25 14897.83 17199.50 4299.36 12199.10 4397.25 21799.28 14296.66 22099.05 11598.71 18197.56 9199.86 7793.00 28199.57 17499.53 91
CHOSEN 280x42095.51 27095.47 26295.65 30998.25 29288.27 32993.25 34298.88 22993.53 29494.65 33297.15 29586.17 29399.93 2697.41 12699.93 3998.73 261
CANet97.87 17497.76 17398.19 21397.75 31295.51 23596.76 24999.05 20097.74 14796.93 27798.21 24095.59 20499.89 5697.86 10499.93 3999.19 208
Fast-Effi-MVS+-dtu98.27 14498.09 15198.81 13498.43 28498.11 10497.61 19299.50 6598.64 9597.39 26297.52 27898.12 6099.95 1396.90 14898.71 27098.38 280
Effi-MVS+-dtu98.26 14697.90 16799.35 6298.02 30499.49 398.02 14999.16 18398.29 11897.64 23997.99 25596.44 17199.95 1396.66 16698.93 26198.60 269
CANet_DTU97.26 21597.06 21197.84 23097.57 31994.65 25496.19 28198.79 24597.23 19695.14 32998.24 23793.22 25599.84 10397.34 12899.84 7399.04 224
MVS_030498.02 16297.88 16998.46 18898.22 29796.39 20296.50 26399.49 7198.03 12697.24 26898.33 23194.80 22899.90 4798.31 8499.95 3099.08 219
MP-MVS-pluss98.57 10898.23 13499.60 1299.69 4299.35 997.16 22999.38 10394.87 27198.97 12898.99 13498.01 6699.88 6397.29 13099.70 13199.58 65
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS98.34 13697.94 16399.54 2599.57 6299.25 1998.57 8698.84 23697.55 16399.31 7997.71 26794.61 23399.88 6396.14 19999.19 23399.48 117
sam_mvs184.74 30598.81 251
sam_mvs84.29 311
semantic-postprocess96.87 27299.27 13491.16 32199.25 15399.10 6599.41 5899.35 6892.91 26199.96 898.65 6699.94 3399.49 111
TSAR-MVS + MP.98.63 9898.49 10299.06 10299.64 5097.90 12898.51 9598.94 21896.96 20599.24 9098.89 15697.83 7699.81 14296.88 14999.49 19799.48 117
xiu_mvs_v1_base_debu97.86 17598.17 13996.92 26998.98 20393.91 27596.45 26699.17 18097.85 14498.41 18997.14 29698.47 3999.92 3498.02 9599.05 24896.92 322
OPM-MVS98.56 10998.32 13099.25 7799.41 11598.73 6497.13 23199.18 17497.10 20398.75 15998.92 14798.18 5699.65 25996.68 16599.56 18199.37 158
ACMMP_Plus98.75 7598.48 10399.57 1699.58 5799.29 1397.82 16999.25 15396.94 20698.78 15599.12 10698.02 6599.84 10397.13 13899.67 14999.59 58
ambc98.24 21098.82 23795.97 21998.62 8199.00 21699.27 8299.21 8796.99 13499.50 30196.55 17699.50 19699.26 191
zzz-MVS98.79 6998.52 9699.61 999.67 4499.36 797.33 21299.20 16498.83 8798.89 14098.90 15196.98 13599.92 3497.16 13499.70 13199.56 75
MTGPAbinary99.20 164
mvs-test197.83 18197.48 19298.89 12598.02 30499.20 2497.20 22399.16 18398.29 11896.46 30197.17 29396.44 17199.92 3496.66 16697.90 31197.54 315
Effi-MVS+98.02 16297.82 17298.62 15998.53 27897.19 17097.33 21299.68 1697.30 18796.68 29097.46 28398.56 3699.80 15496.63 16898.20 29198.86 246
xiu_mvs_v2_base97.16 22397.49 18996.17 29598.54 27692.46 29695.45 31398.84 23697.25 19197.48 25396.49 30598.31 4799.90 4796.34 18998.68 27296.15 338
xiu_mvs_v1_base97.86 17598.17 13996.92 26998.98 20393.91 27596.45 26699.17 18097.85 14498.41 18997.14 29698.47 3999.92 3498.02 9599.05 24896.92 322
new-patchmatchnet98.35 13598.74 6697.18 26099.24 13892.23 30096.42 26999.48 7498.30 11599.69 1799.53 4497.44 10299.82 12998.84 5899.77 10599.49 111
pmmvs699.67 399.70 399.60 1299.90 599.27 1699.53 999.76 799.64 1099.84 999.83 399.50 599.87 7299.36 2899.92 4999.64 40
pmmvs597.64 18997.49 18998.08 22099.14 17295.12 24596.70 25399.05 20093.77 29198.62 17098.83 16593.23 25499.75 20598.33 8399.76 11499.36 164
test_post197.59 19520.48 35883.07 31799.66 25494.16 251
test_post21.25 35783.86 31399.70 231
Fast-Effi-MVS+97.67 18797.38 19898.57 16998.71 24997.43 16097.23 21999.45 8594.82 27396.13 30596.51 30498.52 3899.91 4396.19 19498.83 26398.37 282
patchmatchnet-post98.77 17584.37 30899.85 88
Anonymous2023121199.71 299.70 399.74 299.97 299.52 299.74 499.82 499.73 699.91 499.89 299.27 999.94 2099.02 4999.94 3399.75 21
pmmvs-eth3d98.47 12498.34 12698.86 12999.30 13297.76 14197.16 22999.28 14295.54 25899.42 5799.19 9097.27 11399.63 26297.89 10099.97 2399.20 203
GG-mvs-BLEND94.76 31994.54 35392.13 30199.31 2080.47 35988.73 35391.01 35367.59 35598.16 35182.30 34994.53 34593.98 350
xiu_mvs_v1_base_debi97.86 17598.17 13996.92 26998.98 20393.91 27596.45 26699.17 18097.85 14498.41 18997.14 29698.47 3999.92 3498.02 9599.05 24896.92 322
Anonymous2023120698.21 15198.21 13598.20 21299.51 8495.43 23898.13 12899.32 12996.16 23998.93 13698.82 16896.00 18799.83 11797.32 12999.73 11999.36 164
MTAPA98.88 6198.64 8499.61 999.67 4499.36 798.43 11199.20 16498.83 8798.89 14098.90 15196.98 13599.92 3497.16 13499.70 13199.56 75
MTMP91.91 350
gm-plane-assit94.83 35281.97 35388.07 33994.99 33599.60 27191.76 299
test9_res93.28 27899.15 23999.38 157
MVP-Stereo98.08 16097.92 16598.57 16998.96 20696.79 18597.90 16199.18 17496.41 22898.46 18498.95 14395.93 19399.60 27196.51 17998.98 25899.31 180
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST998.71 24998.08 10895.96 29099.03 20591.40 32095.85 31297.53 27696.52 16699.76 199
train_agg97.10 22596.45 24399.07 9798.71 24998.08 10895.96 29099.03 20591.64 31495.85 31297.53 27696.47 16999.76 19993.67 26799.16 23699.36 164
gg-mvs-nofinetune92.37 32091.20 32495.85 30595.80 35192.38 29899.31 2081.84 35899.75 491.83 34799.74 868.29 35499.02 33987.15 33197.12 32596.16 336
Patchmatch-test196.44 25496.72 22795.60 31098.24 29488.35 32895.85 29996.88 30696.11 24097.67 23898.57 20793.10 25899.69 23594.79 23499.22 22698.77 257
Patchmatch-test96.55 24996.34 24697.17 26198.35 28893.06 29098.40 11397.79 28397.33 18398.41 18998.67 18883.68 31499.69 23595.16 22899.31 21598.77 257
test_898.67 26098.01 11495.91 29699.02 20991.64 31495.79 31497.50 27996.47 16999.76 199
MS-PatchMatch97.68 18697.75 17497.45 25298.23 29693.78 28197.29 21598.84 23696.10 24198.64 16698.65 19296.04 18499.36 31996.84 15299.14 24099.20 203
Patchmatch-RL test97.26 21597.02 21297.99 22799.52 8195.53 23496.13 28299.71 1297.47 16999.27 8299.16 9884.30 31099.62 26497.89 10099.77 10598.81 251
agg_prior396.95 23596.27 24899.00 11298.68 25797.91 12695.96 29099.01 21290.74 32695.60 31597.45 28496.14 18099.74 21493.67 26799.16 23699.36 164
cdsmvs_eth3d_5k24.66 33232.88 3330.00 3470.00 3610.00 3620.00 35399.10 1920.00 3570.00 35897.58 27499.21 110.00 3600.00 3570.00 3580.00 358
pcd_1.5k_mvsjas8.17 33510.90 3360.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 35998.07 610.00 3600.00 3570.00 3580.00 358
pcd1.5k->3k41.59 33144.35 33233.30 34499.87 120.00 3620.00 35399.58 360.00 3570.00 3580.00 35999.70 20.00 3600.00 35799.99 1199.91 2
agg_prior197.06 22896.40 24499.03 10698.68 25797.99 11595.76 30199.01 21291.73 31395.59 31697.50 27996.49 16899.77 19493.71 26699.14 24099.34 170
agg_prior292.50 29399.16 23699.37 158
agg_prior98.68 25797.99 11599.01 21295.59 31699.77 194
tmp_tt78.77 33078.73 33178.90 34258.45 35874.76 35894.20 33478.26 36039.16 35486.71 35492.82 35280.50 32375.19 35786.16 33492.29 35086.74 352
canonicalmvs98.34 13698.26 13398.58 16798.46 28197.82 13698.96 6399.46 8299.19 5497.46 25495.46 32898.59 3299.46 30898.08 9298.71 27098.46 274
anonymousdsp99.51 1299.47 1599.62 699.88 899.08 4799.34 1599.69 1598.93 8399.65 2399.72 1198.93 2099.95 1399.11 44100.00 199.82 10
alignmvs97.35 20896.88 21998.78 13998.54 27698.09 10597.71 17897.69 28899.20 5097.59 24395.90 31888.12 28899.55 28898.18 8998.96 25998.70 264
nrg03099.40 2199.35 2299.54 2599.58 5799.13 3898.98 6299.48 7499.68 799.46 5099.26 7998.62 3099.73 21999.17 4399.92 4999.76 19
v14419298.54 11698.57 9398.45 19099.21 15095.98 21897.63 18999.36 11197.15 20299.32 7799.18 9295.84 19899.84 10399.50 2299.91 5499.54 86
FIs99.14 3799.09 4599.29 7099.70 4098.28 9399.13 4699.52 6399.48 2599.24 9099.41 6196.79 15099.82 12998.69 6599.88 6499.76 19
v192192098.54 11698.60 9198.38 19999.20 15995.76 22897.56 19899.36 11197.23 19699.38 6299.17 9796.02 18599.84 10399.57 1899.90 5799.54 86
UA-Net99.47 1399.40 1799.70 399.49 9299.29 1399.80 399.72 1199.82 299.04 11899.81 498.05 6499.96 898.85 5699.99 1199.86 8
v119298.60 10598.66 8298.41 19399.27 13495.88 22497.52 20299.36 11197.41 17799.33 7299.20 8996.37 17699.82 12999.57 1899.92 4999.55 83
FC-MVSNet-test99.27 2999.25 3499.34 6599.77 2598.37 9199.30 2499.57 4399.61 1899.40 6099.50 4697.12 12599.85 8899.02 4999.94 3399.80 13
v114498.60 10598.66 8298.41 19399.36 12195.90 22397.58 19699.34 12197.51 16599.27 8299.15 10296.34 17799.80 15499.47 2499.93 3999.51 99
sosnet-low-res0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
HFP-MVS98.71 8098.44 11299.51 4099.49 9299.16 2998.52 9199.31 13197.47 16998.58 17798.50 21897.97 7199.85 8896.57 17299.59 16499.53 91
v14898.45 12798.60 9198.00 22699.44 10994.98 24697.44 20899.06 19698.30 11599.32 7798.97 13996.65 15899.62 26498.37 8099.85 7199.39 151
sosnet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
v74899.44 1599.48 1399.33 6799.88 898.43 8799.42 1199.53 5999.63 1299.69 1799.60 3497.99 6999.91 4399.60 1499.96 2899.66 33
uncertanet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
AllTest98.44 12898.20 13699.16 8599.50 8698.55 7798.25 11999.58 3696.80 21298.88 14399.06 11897.65 8599.57 28294.45 24499.61 16199.37 158
TestCases99.16 8599.50 8698.55 7799.58 3696.80 21298.88 14399.06 11897.65 8599.57 28294.45 24499.61 16199.37 158
v7n99.53 1099.57 1099.41 5399.88 898.54 8099.45 1099.61 3099.66 999.68 2099.66 2298.44 4299.95 1399.73 899.96 2899.75 21
v114198.63 9898.70 7498.41 19399.39 11795.96 22097.64 18699.21 16097.92 13099.35 6899.08 11296.61 16299.78 18499.25 3499.90 5799.50 104
region2R98.69 8798.40 11799.54 2599.53 7999.17 2798.52 9199.31 13197.46 17498.44 18698.51 21597.83 7699.88 6396.46 18299.58 17099.58 65
testing_298.93 5798.99 5098.76 14399.57 6297.03 17797.85 16699.13 18798.46 10799.44 5499.44 5798.22 5299.74 21498.85 5699.94 3399.51 99
test_normal97.58 19397.41 19498.10 21699.03 19595.72 22996.21 27897.05 29896.71 21798.65 16498.12 24693.87 24699.69 23597.68 11699.35 20898.88 244
v1neww98.70 8298.76 6398.52 17999.47 9996.30 20798.03 14299.18 17497.92 13099.26 8799.08 11296.91 13899.78 18499.19 4099.82 8299.47 125
PS-MVSNAJss99.46 1499.49 1299.35 6299.90 598.15 10199.20 3599.65 2099.48 2599.92 399.71 1498.07 6199.96 899.53 21100.00 199.93 1
PS-MVSNAJ97.08 22797.39 19796.16 29798.56 27392.46 29695.24 31898.85 23597.25 19197.49 25295.99 31398.07 6199.90 4796.37 18798.67 27396.12 339
jajsoiax99.58 899.61 799.48 4599.87 1298.61 7299.28 2999.66 1999.09 6899.89 899.68 1999.53 499.97 399.50 2299.99 1199.87 6
mvs_tets99.63 599.67 599.49 4499.88 898.61 7299.34 1599.71 1299.27 4599.90 599.74 899.68 399.97 399.55 2099.99 1199.88 5
#test#98.50 12198.16 14299.51 4099.49 9299.16 2998.03 14299.31 13196.30 23398.58 17798.50 21897.97 7199.85 8895.68 22099.59 16499.53 91
EI-MVSNet-UG-set98.69 8798.71 7198.62 15999.10 17596.37 20397.23 21998.87 23099.20 5099.19 9798.99 13497.30 11099.85 8898.77 6299.79 9799.65 37
EI-MVSNet-Vis-set98.68 9098.70 7498.63 15799.09 17896.40 20197.23 21998.86 23499.20 5099.18 10098.97 13997.29 11299.85 8898.72 6499.78 10199.64 40
Regformer-398.61 10498.61 8998.63 15799.02 19796.53 19497.17 22798.84 23699.13 6099.10 10798.85 16297.24 11899.79 17498.41 7999.70 13199.57 70
Regformer-498.73 7898.68 7998.89 12599.02 19797.22 16897.17 22799.06 19699.21 4799.17 10198.85 16297.45 10199.86 7798.48 7599.70 13199.60 52
Regformer-198.55 11398.44 11298.87 12798.85 22997.29 16396.91 24198.99 21798.97 7898.99 12498.64 19597.26 11699.81 14297.79 10599.57 17499.51 99
Regformer-298.60 10598.46 10899.02 10998.85 22997.71 14696.91 24199.09 19398.98 7799.01 12198.64 19597.37 10799.84 10397.75 11199.57 17499.52 97
v7new98.70 8298.76 6398.52 17999.47 9996.30 20798.03 14299.18 17497.92 13099.26 8799.08 11296.91 13899.78 18499.19 4099.82 8299.47 125
HPM-MVS++copyleft98.10 15897.64 18299.48 4599.09 17899.13 3897.52 20298.75 25097.46 17496.90 28297.83 26296.01 18699.84 10395.82 21499.35 20899.46 129
test_prior497.97 12095.86 297
XVS98.72 7998.45 11099.53 3299.46 10399.21 2298.65 7899.34 12198.62 9797.54 24898.63 19997.50 9699.83 11796.79 15499.53 18899.56 75
v124098.55 11398.62 8698.32 20399.22 14495.58 23297.51 20499.45 8597.16 20099.45 5399.24 8296.12 18299.85 8899.60 1499.88 6499.55 83
test_prior397.48 20297.00 21398.95 11698.69 25597.95 12395.74 30399.03 20596.48 22596.11 30697.63 27295.92 19499.59 27594.16 25199.20 22999.30 183
v1899.02 4699.17 3998.57 16999.45 10696.31 20598.94 6499.58 3699.06 7099.43 5599.58 3896.91 13899.80 15499.60 1499.97 2399.59 58
pm-mvs199.44 1599.48 1399.33 6799.80 2298.63 6999.29 2599.63 2599.30 4299.65 2399.60 3499.16 1699.82 12999.07 4699.83 7999.56 75
test_prior295.74 30396.48 22596.11 30697.63 27295.92 19494.16 25199.20 229
X-MVStestdata94.32 29792.59 31499.53 3299.46 10399.21 2298.65 7899.34 12198.62 9797.54 24845.85 35497.50 9699.83 11796.79 15499.53 18899.56 75
test_prior98.95 11698.69 25597.95 12399.03 20599.59 27599.30 183
v1799.07 4399.22 3698.61 16299.50 8696.42 19999.01 5599.60 3299.15 5699.48 4699.61 3097.05 12899.81 14299.64 1299.98 1999.61 49
v1699.07 4399.22 3698.61 16299.50 8696.42 19999.01 5599.60 3299.15 5699.46 5099.61 3097.04 12999.81 14299.64 1299.97 2399.61 49
divwei89l23v2f11298.63 9898.70 7498.41 19399.39 11795.96 22097.64 18699.21 16097.92 13099.35 6899.08 11296.61 16299.78 18499.25 3499.90 5799.50 104
v1599.11 4199.27 3398.62 15999.52 8196.43 19899.01 5599.63 2599.18 5599.59 3299.64 2697.13 12499.81 14299.71 10100.00 199.64 40
旧先验295.76 30188.56 33897.52 25099.66 25494.48 242
新几何295.93 294
新几何198.91 12298.94 20997.76 14198.76 24787.58 34196.75 28998.10 24894.80 22899.78 18492.73 29099.00 25599.20 203
旧先验198.82 23797.45 15998.76 24798.34 22995.50 20899.01 25499.23 197
无先验95.74 30398.74 25289.38 33499.73 21992.38 29599.22 201
原ACMM295.53 310
原ACMM198.35 20198.90 21996.25 21098.83 24192.48 30596.07 30998.10 24895.39 21199.71 22992.61 29298.99 25699.08 219
v1399.24 3199.39 1898.77 14199.63 5296.79 18599.24 3399.65 2099.39 3399.62 2799.70 1697.50 9699.84 10399.78 5100.00 199.67 31
v1299.21 3299.37 2098.74 14999.60 5596.72 19099.19 3999.65 2099.35 3999.62 2799.69 1797.43 10399.83 11799.76 6100.00 199.66 33
test22298.92 21596.93 18295.54 30998.78 24685.72 34596.86 28598.11 24794.43 23699.10 24799.23 197
testdata299.79 17492.80 288
segment_acmp97.02 132
testdata98.09 21798.93 21195.40 23998.80 24490.08 33197.45 25598.37 22695.26 21399.70 23193.58 27198.95 26099.17 213
testdata195.44 31496.32 231
v899.01 4799.16 4198.57 16999.47 9996.31 20598.90 6799.47 8099.03 7299.52 3999.57 3996.93 13799.81 14299.60 1499.98 1999.60 52
131495.74 26495.60 26196.17 29597.53 32292.75 29398.07 13698.31 27191.22 32294.25 33696.68 30295.53 20599.03 33891.64 30297.18 32496.74 330
112196.73 24396.00 25198.91 12298.95 20897.76 14198.07 13698.73 25387.65 34096.54 29498.13 24294.52 23599.73 21992.38 29599.02 25299.24 196
LFMVS97.20 22096.72 22798.64 15598.72 24796.95 18198.93 6694.14 33699.74 598.78 15599.01 13184.45 30799.73 21997.44 12499.27 22199.25 193
v798.67 9298.73 6798.50 18499.43 11396.21 21198.00 15199.31 13197.58 15899.17 10199.18 9296.63 15999.80 15499.42 2799.88 6499.48 117
v698.70 8298.76 6398.52 17999.47 9996.30 20798.03 14299.18 17497.92 13099.27 8299.08 11296.91 13899.78 18499.19 4099.82 8299.48 117
VDD-MVS98.56 10998.39 11999.07 9799.13 17398.07 11098.59 8597.01 29999.59 1999.11 10599.27 7794.82 22599.79 17498.34 8199.63 15699.34 170
v1199.12 4099.31 2898.53 17899.59 5696.11 21399.08 4999.65 2099.15 5699.60 3099.69 1797.26 11699.83 11799.81 3100.00 199.66 33
VDDNet98.21 15197.95 16199.01 11099.58 5797.74 14499.01 5597.29 29499.67 898.97 12899.50 4690.45 27799.80 15497.88 10299.20 22999.48 117
v5299.59 699.60 899.55 2099.87 1299.00 4899.59 799.56 4999.56 2299.68 2099.72 1198.57 3499.93 2699.85 199.99 1199.72 24
V1499.14 3799.30 3198.66 15399.56 6996.53 19499.08 4999.63 2599.24 4699.60 3099.66 2297.23 12099.82 12999.73 8100.00 199.65 37
v1098.97 5499.11 4498.55 17499.44 10996.21 21198.90 6799.55 5498.73 9399.48 4699.60 3496.63 15999.83 11799.70 1199.99 1199.61 49
V499.59 699.60 899.55 2099.87 1299.00 4899.59 799.56 4999.56 2299.68 2099.72 1198.57 3499.93 2699.85 199.99 1199.72 24
VPNet98.87 6298.83 5599.01 11099.70 4097.62 15298.43 11199.35 11799.47 2799.28 8099.05 12396.72 15599.82 12998.09 9199.36 20699.59 58
MVS93.19 31592.09 31996.50 28596.91 33794.03 27198.07 13698.06 27968.01 35294.56 33496.48 30695.96 19299.30 32783.84 34396.89 32996.17 335
v2v48298.56 10998.62 8698.37 20099.42 11495.81 22797.58 19699.16 18397.90 13899.28 8099.01 13195.98 19199.79 17499.33 2999.90 5799.51 99
v198.63 9898.70 7498.41 19399.39 11795.96 22097.64 18699.20 16497.92 13099.36 6699.07 11796.63 15999.78 18499.25 3499.90 5799.50 104
V4298.78 7298.78 6098.76 14399.44 10997.04 17698.27 11899.19 17097.87 14299.25 8999.16 9896.84 14599.78 18499.21 3899.84 7399.46 129
V999.18 3499.34 2498.70 15099.58 5796.63 19399.14 4499.64 2499.30 4299.61 2999.68 1997.33 10899.83 11799.75 7100.00 199.65 37
SD-MVS98.40 13298.68 7997.54 24898.96 20697.99 11597.88 16299.36 11198.20 12199.63 2699.04 12598.76 2495.33 35596.56 17599.74 11699.31 180
GA-MVS95.86 26295.32 26797.49 25098.60 27094.15 26993.83 33997.93 28195.49 25996.68 29097.42 28683.21 31599.30 32796.22 19298.55 27999.01 228
MSLP-MVS++98.02 16298.14 14697.64 24298.58 27195.19 24297.48 20599.23 15997.47 16997.90 21298.62 20197.04 12998.81 34797.55 11799.41 20298.94 237
APDe-MVS98.99 4998.79 5999.60 1299.21 15099.15 3498.87 6999.48 7497.57 16099.35 6899.24 8297.83 7699.89 5697.88 10299.70 13199.75 21
APD-MVS_3200maxsize98.84 6598.61 8999.53 3299.19 16099.27 1698.49 9799.33 12698.64 9599.03 12098.98 13797.89 7499.85 8896.54 17799.42 20199.46 129
ADS-MVSNet295.43 27194.98 27696.76 27798.14 30091.74 30397.92 15897.76 28490.23 32796.51 29798.91 14885.61 29999.85 8892.88 28496.90 32798.69 265
EI-MVSNet98.40 13298.51 9798.04 22499.10 17594.73 25097.20 22398.87 23098.97 7899.06 11099.02 12996.00 18799.80 15498.58 6899.82 8299.60 52
Regformer0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
CVMVSNet96.25 25797.21 20593.38 33599.10 17580.56 35597.20 22398.19 27696.94 20699.00 12399.02 12989.50 28299.80 15496.36 18899.59 16499.78 15
pmmvs497.58 19397.28 20398.51 18398.84 23296.93 18295.40 31598.52 26393.60 29398.61 17298.65 19295.10 21799.60 27196.97 14499.79 9798.99 230
EU-MVSNet97.66 18898.50 9995.13 31599.63 5285.84 33798.35 11598.21 27398.23 12099.54 3599.46 5295.02 21899.68 24098.24 8599.87 6899.87 6
VNet98.42 12998.30 13198.79 13698.79 24297.29 16398.23 12098.66 25799.31 4198.85 14698.80 17094.80 22899.78 18498.13 9099.13 24399.31 180
test-LLR93.90 30893.85 29894.04 32696.53 34284.62 34594.05 33592.39 34796.17 23694.12 33895.07 33282.30 31999.67 24695.87 21098.18 29297.82 296
TESTMET0.1,192.19 32391.77 32293.46 33396.48 34482.80 35294.05 33591.52 35294.45 28094.00 34194.88 34066.65 35799.56 28595.78 21598.11 29798.02 290
test-mter92.33 32191.76 32394.04 32696.53 34284.62 34594.05 33592.39 34794.00 29094.12 33895.07 33265.63 36099.67 24695.87 21098.18 29297.82 296
VPA-MVSNet99.30 2899.30 3199.28 7199.49 9298.36 9299.00 5999.45 8599.63 1299.52 3999.44 5798.25 4899.88 6399.09 4599.84 7399.62 45
ACMMPR98.70 8298.42 11599.54 2599.52 8199.14 3598.52 9199.31 13197.47 16998.56 17998.54 21397.75 8199.88 6396.57 17299.59 16499.58 65
testgi98.32 13898.39 11998.13 21599.57 6295.54 23397.78 17099.49 7197.37 18099.19 9797.65 27198.96 1999.49 30296.50 18098.99 25699.34 170
test20.0398.78 7298.77 6298.78 13999.46 10397.20 16997.78 17099.24 15799.04 7199.41 5898.90 15197.65 8599.76 19997.70 11299.79 9799.39 151
thres600view794.45 29493.83 29996.29 28799.06 18591.53 30697.99 15294.24 33298.34 11097.44 25695.01 33479.84 32999.67 24684.33 34198.23 28897.66 305
111193.99 30693.72 30294.80 31899.33 12885.20 34195.97 28699.39 10097.88 14098.64 16698.56 21057.79 36199.80 15496.02 20199.87 6899.40 150
.test124579.71 32984.30 33065.96 34399.33 12885.20 34195.97 28699.39 10097.88 14098.64 16698.56 21057.79 36199.80 15496.02 20115.07 35512.86 356
ADS-MVSNet95.24 27394.93 27796.18 29498.14 30090.10 32397.92 15897.32 29390.23 32796.51 29798.91 14885.61 29999.74 21492.88 28496.90 32798.69 265
MP-MVScopyleft98.46 12698.09 15199.54 2599.57 6299.22 2198.50 9699.19 17097.61 15697.58 24498.66 19097.40 10599.88 6394.72 23899.60 16399.54 86
testmvs17.12 33320.53 3346.87 34612.05 3594.20 36193.62 3406.73 3614.62 35610.41 35624.33 3558.28 3643.56 3599.69 35615.07 35512.86 356
thres40094.14 30293.44 30896.24 29398.93 21191.44 30897.60 19394.29 33097.94 12897.10 27094.31 34579.67 33399.62 26483.05 34498.08 30597.66 305
test12317.04 33420.11 3357.82 34510.25 3604.91 36094.80 3264.47 3624.93 35510.00 35724.28 3569.69 3633.64 35810.14 35512.43 35714.92 355
thres20093.72 31093.14 31195.46 31298.66 26591.29 31896.61 26094.63 32497.39 17996.83 28693.71 34879.88 32899.56 28582.40 34898.13 29695.54 343
test0.0.03 194.51 29393.69 30396.99 26796.05 34893.61 28594.97 32393.49 33796.17 23697.57 24694.88 34082.30 31999.01 34193.60 27094.17 34898.37 282
test1235694.85 28395.12 27394.03 32898.25 29283.12 35093.85 33899.33 12694.17 28897.28 26697.20 29185.83 29799.75 20590.85 31999.33 21199.22 201
testus95.52 26895.32 26796.13 29997.91 30989.49 32593.62 34099.61 3092.41 30697.38 26495.42 33094.72 23299.63 26288.06 32998.72 26799.26 191
pmmvs395.03 27694.40 28596.93 26897.70 31692.53 29595.08 32197.71 28788.57 33797.71 23598.08 25179.39 33599.82 12996.19 19499.11 24698.43 277
testmv98.51 12098.47 10598.61 16299.24 13896.53 19496.66 25699.73 1098.56 10599.50 4499.23 8697.24 11899.87 7296.16 19799.93 3999.44 135
EMVS93.83 30994.02 29693.23 33696.83 34084.96 34389.77 35196.32 31597.92 13097.43 25796.36 30986.17 29398.93 34387.68 33097.73 31495.81 341
E-PMN94.17 30194.37 28693.58 33296.86 33885.71 33990.11 35097.07 29798.17 12497.82 22497.19 29284.62 30698.94 34289.77 32397.68 31596.09 340
test235691.64 32690.19 32996.00 30094.30 35489.58 32490.84 34896.68 30991.76 31295.48 32593.69 34967.05 35699.52 29584.83 34097.08 32698.91 241
test123567897.06 22896.84 22297.73 23698.55 27594.46 26394.80 32699.36 11196.85 21198.83 14998.26 23592.72 26499.82 12992.49 29499.70 13198.91 241
PGM-MVS98.66 9398.37 12299.55 2099.53 7999.18 2698.23 12099.49 7197.01 20498.69 16298.88 15798.00 6799.89 5695.87 21099.59 16499.58 65
LCM-MVSNet-Re98.64 9698.48 10399.11 9198.85 22998.51 8298.49 9799.83 398.37 10899.69 1799.46 5298.21 5499.92 3494.13 25599.30 21698.91 241
LCM-MVSNet99.93 199.92 199.94 199.99 199.97 199.90 199.89 299.98 199.99 199.96 199.77 1100.00 199.81 3100.00 199.85 9
MCST-MVS98.00 16597.63 18399.10 9399.24 13898.17 10096.89 24398.73 25395.66 25097.92 20997.70 26897.17 12399.66 25496.18 19699.23 22599.47 125
mvs_anonymous97.83 18198.16 14296.87 27298.18 29991.89 30297.31 21498.90 22797.37 18098.83 14999.46 5296.28 17899.79 17498.90 5398.16 29498.95 235
MVS_Test98.18 15498.36 12397.67 23898.48 27994.73 25098.18 12499.02 20997.69 15098.04 20699.11 10797.22 12299.56 28598.57 7098.90 26298.71 262
MDA-MVSNet-bldmvs97.94 16997.91 16698.06 22299.44 10994.96 24796.63 25899.15 18698.35 10998.83 14999.11 10794.31 23999.85 8896.60 16998.72 26799.37 158
CDPH-MVS97.26 21596.66 23499.07 9799.00 20098.15 10196.03 28499.01 21291.21 32397.79 23197.85 26196.89 14399.69 23592.75 28999.38 20599.39 151
test1298.93 11998.58 27197.83 13398.66 25796.53 29595.51 20799.69 23599.13 24399.27 188
diffmvs97.49 19997.36 19997.91 22898.38 28795.70 23197.95 15699.31 13194.87 27196.14 30498.78 17394.84 22499.43 31297.69 11498.26 28798.59 270
YYNet197.60 19197.67 17797.39 25699.04 19293.04 29295.27 31698.38 26997.25 19198.92 13798.95 14395.48 20999.73 21996.99 14398.74 26699.41 145
PMMVS298.07 16198.08 15498.04 22499.41 11594.59 25694.59 33099.40 9897.50 16698.82 15298.83 16596.83 14699.84 10397.50 12199.81 8999.71 27
MDA-MVSNet_test_wron97.60 19197.66 18097.41 25599.04 19293.09 28995.27 31698.42 26797.26 19098.88 14398.95 14395.43 21099.73 21997.02 14298.72 26799.41 145
tpmvs95.02 27795.25 26994.33 32396.39 34685.87 33698.08 13496.83 30795.46 26095.51 32498.69 18485.91 29699.53 29194.16 25196.23 33597.58 313
PM-MVS98.82 6698.72 7099.12 9099.64 5098.54 8097.98 15399.68 1697.62 15499.34 7199.18 9297.54 9499.77 19497.79 10599.74 11699.04 224
HQP_MVS97.99 16797.67 17798.93 11999.19 16097.65 14997.77 17299.27 14798.20 12197.79 23197.98 25694.90 22099.70 23194.42 24699.51 19199.45 133
plane_prior799.19 16097.87 130
plane_prior698.99 20297.70 14794.90 220
plane_prior599.27 14799.70 23194.42 24699.51 19199.45 133
plane_prior497.98 256
plane_prior397.78 14097.41 17797.79 231
plane_prior297.77 17298.20 121
plane_prior199.05 190
plane_prior97.65 14997.07 23296.72 21599.36 206
PS-CasMVS99.40 2199.33 2699.62 699.71 3499.10 4399.29 2599.53 5999.53 2499.46 5099.41 6198.23 5099.95 1398.89 5599.95 3099.81 12
UniMVSNet_NR-MVSNet98.86 6498.68 7999.40 5599.17 16598.74 6197.68 18199.40 9899.14 5999.06 11098.59 20596.71 15699.93 2698.57 7099.77 10599.53 91
PEN-MVS99.41 2099.34 2499.62 699.73 2899.14 3599.29 2599.54 5899.62 1699.56 3399.42 5998.16 5799.96 898.78 5999.93 3999.77 16
TransMVSNet (Re)99.44 1599.47 1599.36 5799.80 2298.58 7599.27 3199.57 4399.39 3399.75 1299.62 2899.17 1499.83 11799.06 4799.62 15799.66 33
DTE-MVSNet99.43 1899.35 2299.66 499.71 3499.30 1299.31 2099.51 6499.64 1099.56 3399.46 5298.23 5099.97 398.78 5999.93 3999.72 24
DU-MVS98.82 6698.63 8599.39 5699.16 16798.74 6197.54 20199.25 15398.84 8699.06 11098.76 17796.76 15399.93 2698.57 7099.77 10599.50 104
UniMVSNet (Re)98.87 6298.71 7199.35 6299.24 13898.73 6497.73 17799.38 10398.93 8399.12 10498.73 17996.77 15199.86 7798.63 6799.80 9399.46 129
CP-MVSNet99.21 3299.09 4599.56 1899.65 4798.96 5499.13 4699.34 12199.42 3199.33 7299.26 7997.01 13399.94 2098.74 6399.93 3999.79 14
WR-MVS_H99.33 2799.22 3699.65 599.71 3499.24 2099.32 1799.55 5499.46 2899.50 4499.34 7097.30 11099.93 2698.90 5399.93 3999.77 16
WR-MVS98.40 13298.19 13899.03 10699.00 20097.65 14996.85 24598.94 21898.57 10398.89 14098.50 21895.60 20399.85 8897.54 11899.85 7199.59 58
NR-MVSNet98.95 5698.82 5699.36 5799.16 16798.72 6699.22 3499.20 16499.10 6599.72 1398.76 17796.38 17599.86 7798.00 9899.82 8299.50 104
Baseline_NR-MVSNet98.98 5398.86 5399.36 5799.82 2098.55 7797.47 20799.57 4399.37 3699.21 9599.61 3096.76 15399.83 11798.06 9399.83 7999.71 27
TranMVSNet+NR-MVSNet99.17 3599.07 4799.46 5099.37 12098.87 5698.39 11499.42 9699.42 3199.36 6699.06 11898.38 4499.95 1398.34 8199.90 5799.57 70
TSAR-MVS + GP.98.18 15497.98 15998.77 14198.71 24997.88 12996.32 27398.66 25796.33 23099.23 9398.51 21597.48 10099.40 31497.16 13499.46 19899.02 227
abl_698.99 4998.78 6099.61 999.45 10699.46 498.60 8399.50 6598.59 9999.24 9099.04 12598.54 3799.89 5696.45 18399.62 15799.50 104
n20.00 363
nn0.00 363
mPP-MVS98.64 9698.34 12699.54 2599.54 7799.17 2798.63 8099.24 15797.47 16998.09 20298.68 18697.62 8999.89 5696.22 19299.62 15799.57 70
door-mid99.57 43
DI_MVS_plusplus_test97.57 19597.40 19598.07 22199.06 18595.71 23096.58 26196.96 30096.71 21798.69 16298.13 24293.81 24999.68 24097.45 12399.19 23398.80 254
XVG-OURS-SEG-HR98.49 12298.28 13299.14 8899.49 9298.83 5796.54 26299.48 7497.32 18599.11 10598.61 20399.33 899.30 32796.23 19198.38 28599.28 187
DWT-MVSNet_test92.75 31892.05 32094.85 31796.48 34487.21 33397.83 16894.99 32192.22 31092.72 34594.11 34770.75 35299.46 30895.01 23094.33 34797.87 294
MVSFormer98.26 14698.43 11497.77 23398.88 22493.89 27899.39 1399.56 4999.11 6198.16 19798.13 24293.81 24999.97 399.26 3299.57 17499.43 140
jason97.45 20497.35 20197.76 23499.24 13893.93 27495.86 29798.42 26794.24 28698.50 18398.13 24294.82 22599.91 4397.22 13299.73 11999.43 140
jason: jason.
lupinMVS97.06 22896.86 22097.65 24098.88 22493.89 27895.48 31297.97 28093.53 29498.16 19797.58 27493.81 24999.91 4396.77 15699.57 17499.17 213
test_djsdf99.52 1199.51 1199.53 3299.86 1698.74 6199.39 1399.56 4999.11 6199.70 1599.73 1099.00 1799.97 399.26 3299.98 1999.89 3
Test497.43 20597.18 20698.18 21499.05 19096.02 21796.62 25999.09 19396.25 23498.63 16997.70 26890.49 27699.68 24097.50 12199.30 21698.83 248
HPM-MVS_fast99.01 4798.82 5699.57 1699.71 3499.35 999.00 5999.50 6597.33 18398.94 13598.86 16098.75 2599.82 12997.53 11999.71 12899.56 75
PatchFormer-LS_test94.08 30493.91 29794.59 32196.93 33686.86 33497.55 20096.57 31294.27 28594.38 33593.64 35080.96 32199.59 27596.44 18594.48 34697.31 319
testpf89.08 32890.27 32885.50 34194.03 35582.85 35196.87 24491.09 35391.61 31690.96 35094.86 34366.15 35995.83 35294.58 24092.27 35177.82 353
K. test v398.00 16597.66 18099.03 10699.79 2497.56 15399.19 3992.47 34699.62 1699.52 3999.66 2289.61 28099.96 899.25 3499.81 8999.56 75
lessismore_v098.97 11499.73 2897.53 15586.71 35599.37 6499.52 4589.93 27899.92 3498.99 5199.72 12499.44 135
SixPastTwentyTwo98.75 7598.62 8699.16 8599.83 1997.96 12299.28 2998.20 27499.37 3699.70 1599.65 2592.65 26599.93 2699.04 4899.84 7399.60 52
OurMVSNet-221017-099.37 2499.31 2899.53 3299.91 498.98 5099.63 699.58 3699.44 3099.78 1099.76 696.39 17399.92 3499.44 2699.92 4999.68 30
HPM-MVScopyleft98.79 6998.53 9599.59 1599.65 4799.29 1399.16 4299.43 9396.74 21498.61 17298.38 22598.62 3099.87 7296.47 18199.67 14999.59 58
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS98.53 11898.34 12699.11 9199.50 8698.82 5995.97 28699.50 6597.30 18799.05 11598.98 13799.35 799.32 32495.72 21799.68 14399.18 209
XVG-ACMP-BASELINE98.56 10998.34 12699.22 8099.54 7798.59 7497.71 17899.46 8297.25 19198.98 12698.99 13497.54 9499.84 10395.88 20799.74 11699.23 197
LPG-MVS_test98.71 8098.46 10899.47 4899.57 6298.97 5198.23 12099.48 7496.60 22399.10 10799.06 11898.71 2799.83 11795.58 22499.78 10199.62 45
LGP-MVS_train99.47 4899.57 6298.97 5199.48 7496.60 22399.10 10799.06 11898.71 2799.83 11795.58 22499.78 10199.62 45
test1198.87 230
door99.41 97
EPNet_dtu94.93 27894.78 27995.38 31393.58 35687.68 33196.78 24795.69 32097.35 18289.14 35298.09 25088.15 28799.49 30294.95 23399.30 21698.98 231
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268897.49 19997.14 21098.54 17799.68 4396.09 21696.50 26399.62 2891.58 31798.84 14898.97 13992.36 26799.88 6396.76 15799.95 3099.67 31
EPNet96.14 25895.44 26498.25 20990.76 35795.50 23697.92 15894.65 32398.97 7892.98 34498.85 16289.12 28499.87 7295.99 20399.68 14399.39 151
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS96.79 185
HQP-NCC98.67 26096.29 27496.05 24295.55 320
ACMP_Plane98.67 26096.29 27496.05 24295.55 320
APD-MVScopyleft98.10 15897.67 17799.42 5199.11 17498.93 5597.76 17499.28 14294.97 26898.72 16198.77 17597.04 12999.85 8893.79 26599.54 18499.49 111
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS92.82 286
HQP4-MVS95.56 31999.54 28999.32 176
HQP3-MVS99.04 20399.26 223
HQP2-MVS93.84 247
LP96.60 24896.57 23996.68 27897.64 31891.70 30498.11 13197.74 28597.29 18997.91 21199.24 8288.35 28699.85 8897.11 14095.76 33898.49 273
CNVR-MVS98.17 15697.87 17099.07 9798.67 26098.24 9597.01 23498.93 22197.25 19197.62 24098.34 22997.27 11399.57 28296.42 18699.33 21199.39 151
NCCC97.86 17597.47 19399.05 10398.61 26898.07 11096.98 23598.90 22797.63 15397.04 27497.93 25995.99 19099.66 25495.31 22798.82 26499.43 140
114514_t96.50 25295.77 25598.69 15199.48 9797.43 16097.84 16799.55 5481.42 35096.51 29798.58 20695.53 20599.67 24693.41 27699.58 17098.98 231
CP-MVS98.70 8298.42 11599.52 3899.36 12199.12 4098.72 7799.36 11197.54 16498.30 19498.40 22497.86 7599.89 5696.53 17899.72 12499.56 75
DSMNet-mixed97.42 20697.60 18596.87 27299.15 17191.46 30798.54 9099.12 18992.87 30197.58 24499.63 2796.21 17999.90 4795.74 21699.54 18499.27 188
tpm293.09 31692.58 31594.62 32097.56 32086.53 33597.66 18395.79 31986.15 34494.07 34098.23 23975.95 34999.53 29190.91 31796.86 33097.81 298
NP-MVS98.84 23297.39 16296.84 299
EG-PatchMatch MVS98.99 4999.01 4898.94 11899.50 8697.47 15798.04 14199.59 3498.15 12599.40 6099.36 6798.58 3399.76 19998.78 5999.68 14399.59 58
tpm cat193.29 31493.13 31293.75 33097.39 32984.74 34497.39 20997.65 28983.39 34994.16 33798.41 22382.86 31899.39 31691.56 30595.35 34197.14 321
SteuartSystems-ACMMP98.79 6998.54 9499.54 2599.73 2899.16 2998.23 12099.31 13197.92 13098.90 13898.90 15198.00 6799.88 6396.15 19899.72 12499.58 65
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e2392.91 31792.45 31694.29 32497.41 32785.62 34097.95 15696.77 30887.55 34291.33 34998.57 20774.21 35199.59 27591.62 30396.64 33197.65 312
CostFormer93.97 30793.78 30094.51 32297.53 32285.83 33897.98 15395.96 31789.29 33594.99 33198.63 19978.63 33799.62 26494.54 24196.50 33298.09 288
CR-MVSNet96.28 25695.95 25397.28 25797.71 31494.22 26598.11 13198.92 22492.31 30896.91 28099.37 6585.44 30299.81 14297.39 12797.36 32197.81 298
JIA-IIPM95.52 26895.03 27597.00 26696.85 33994.03 27196.93 23895.82 31899.20 5094.63 33399.71 1483.09 31699.60 27194.42 24694.64 34397.36 318
Patchmtry97.35 20896.97 21498.50 18497.31 33196.47 19798.18 12498.92 22498.95 8298.78 15599.37 6585.44 30299.85 8895.96 20599.83 7999.17 213
PatchT96.65 24596.35 24597.54 24897.40 32895.32 24097.98 15396.64 31199.33 4096.89 28399.42 5984.32 30999.81 14297.69 11497.49 31697.48 316
tpmrst95.07 27595.46 26393.91 32997.11 33484.36 34797.62 19096.96 30094.98 26796.35 30298.80 17085.46 30199.59 27595.60 22296.23 33597.79 301
BH-w/o95.13 27494.89 27895.86 30498.20 29891.31 31795.65 30697.37 29193.64 29296.52 29695.70 31993.04 25999.02 33988.10 32895.82 33797.24 320
tpm94.67 29294.34 28795.66 30897.68 31788.42 32797.88 16294.90 32294.46 27896.03 31198.56 21078.66 33699.79 17495.88 20795.01 34298.78 256
DELS-MVS98.27 14498.20 13698.48 18698.86 22696.70 19195.60 30899.20 16497.73 14898.45 18598.71 18197.50 9699.82 12998.21 8799.59 16498.93 238
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
BH-untuned96.83 23896.75 22697.08 26298.74 24593.33 28896.71 25298.26 27296.72 21598.44 18697.37 28995.20 21499.47 30691.89 29897.43 31898.44 276
RPMNet96.82 24096.66 23497.28 25797.71 31494.22 26598.11 13196.90 30599.37 3696.91 28099.34 7086.72 29099.81 14297.53 11997.36 32197.81 298
no-one97.98 16898.10 15097.61 24399.55 7393.82 28096.70 25398.94 21896.18 23599.52 3999.41 6195.90 19699.81 14296.72 16099.99 1199.20 203
MVSTER96.86 23796.55 24097.79 23297.91 30994.21 26797.56 19898.87 23097.49 16899.06 11099.05 12380.72 32299.80 15498.44 7699.82 8299.37 158
CPTT-MVS97.84 18097.36 19999.27 7499.31 13098.46 8598.29 11699.27 14794.90 27097.83 22298.37 22694.90 22099.84 10393.85 26499.54 18499.51 99
GBi-Net98.65 9498.47 10599.17 8298.90 21998.24 9599.20 3599.44 8898.59 9998.95 13199.55 4194.14 24299.86 7797.77 10799.69 13899.41 145
PVSNet_Blended_VisFu98.17 15698.15 14498.22 21199.73 2895.15 24397.36 21199.68 1694.45 28098.99 12499.27 7796.87 14499.94 2097.13 13899.91 5499.57 70
PVSNet_BlendedMVS97.55 19697.53 18797.60 24498.92 21593.77 28296.64 25799.43 9394.49 27697.62 24099.18 9296.82 14799.67 24694.73 23699.93 3999.36 164
UnsupCasMVSNet_eth97.89 17197.60 18598.75 14599.31 13097.17 17297.62 19099.35 11798.72 9498.76 15898.68 18692.57 26699.74 21497.76 11095.60 33999.34 170
UnsupCasMVSNet_bld97.30 21296.92 21698.45 19099.28 13396.78 18996.20 28099.27 14795.42 26198.28 19598.30 23393.16 25699.71 22994.99 23197.37 31998.87 245
PVSNet_Blended96.88 23696.68 23197.47 25198.92 21593.77 28294.71 32899.43 9390.98 32497.62 24097.36 29096.82 14799.67 24694.73 23699.56 18198.98 231
FMVSNet596.01 26095.20 27198.41 19397.53 32296.10 21498.74 7599.50 6597.22 19998.03 20799.04 12569.80 35399.88 6397.27 13199.71 12899.25 193
test198.65 9498.47 10599.17 8298.90 21998.24 9599.20 3599.44 8898.59 9998.95 13199.55 4194.14 24299.86 7797.77 10799.69 13899.41 145
new_pmnet96.99 23396.76 22597.67 23898.72 24794.89 24895.95 29398.20 27492.62 30498.55 18098.54 21394.88 22399.52 29593.96 25999.44 20098.59 270
FMVSNet397.50 19797.24 20498.29 20798.08 30295.83 22697.86 16598.91 22697.89 13998.95 13198.95 14387.06 28999.81 14297.77 10799.69 13899.23 197
dp93.47 31293.59 30693.13 33796.64 34181.62 35497.66 18396.42 31492.80 30296.11 30698.64 19578.55 33899.59 27593.31 27792.18 35298.16 285
FMVSNet298.49 12298.40 11798.75 14598.90 21997.14 17598.61 8299.13 18798.59 9999.19 9799.28 7594.14 24299.82 12997.97 9999.80 9399.29 186
FMVSNet199.17 3599.17 3999.17 8299.55 7398.24 9599.20 3599.44 8899.21 4799.43 5599.55 4197.82 7999.86 7798.42 7899.89 6399.41 145
N_pmnet97.63 19097.17 20798.99 11399.27 13497.86 13195.98 28593.41 33895.25 26399.47 4998.90 15195.63 20299.85 8896.91 14699.73 11999.27 188
cascas94.79 28794.33 28896.15 29896.02 35092.36 29992.34 34799.26 15285.34 34695.08 33094.96 33992.96 26098.53 34894.41 24998.59 27797.56 314
BH-RMVSNet96.83 23896.58 23897.58 24698.47 28094.05 27096.67 25597.36 29296.70 21997.87 21497.98 25695.14 21699.44 31190.47 32198.58 27899.25 193
UGNet98.53 11898.45 11098.79 13697.94 30796.96 18099.08 4998.54 26299.10 6596.82 28799.47 5196.55 16599.84 10398.56 7399.94 3399.55 83
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
WTY-MVS96.67 24496.27 24897.87 22998.81 23994.61 25596.77 24897.92 28294.94 26997.12 26997.74 26691.11 27499.82 12993.89 26198.15 29599.18 209
XXY-MVS99.14 3799.15 4399.10 9399.76 2697.74 14498.85 7299.62 2898.48 10699.37 6499.49 4998.75 2599.86 7798.20 8899.80 9399.71 27
sss97.21 21996.93 21598.06 22298.83 23495.22 24196.75 25098.48 26594.49 27697.27 26797.90 26092.77 26399.80 15496.57 17299.32 21399.16 216
Test_1112_low_res96.99 23396.55 24098.31 20599.35 12595.47 23795.84 30099.53 5991.51 31996.80 28898.48 22191.36 27399.83 11796.58 17099.53 18899.62 45
1112_ss97.29 21496.86 22098.58 16799.34 12796.32 20496.75 25099.58 3693.14 29896.89 28397.48 28192.11 27099.86 7796.91 14699.54 18499.57 70
ab-mvs-re8.12 33610.83 3370.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 35897.48 2810.00 3650.00 3600.00 3570.00 3580.00 358
ab-mvs98.41 13098.36 12398.59 16699.19 16097.23 16699.32 1798.81 24297.66 15198.62 17099.40 6496.82 14799.80 15495.88 20799.51 19198.75 260
TR-MVS95.55 26795.12 27396.86 27597.54 32193.94 27396.49 26596.53 31394.36 28397.03 27596.61 30394.26 24199.16 33586.91 33296.31 33497.47 317
MDTV_nov1_ep13_2view74.92 35797.69 18090.06 33297.75 23485.78 29893.52 27298.69 265
MDTV_nov1_ep1395.22 27097.06 33583.20 34997.74 17696.16 31694.37 28296.99 27698.83 16583.95 31299.53 29193.90 26097.95 310
MIMVSNet199.38 2399.32 2799.55 2099.86 1699.19 2599.41 1299.59 3499.59 1999.71 1499.57 3997.12 12599.90 4799.21 3899.87 6899.54 86
MIMVSNet96.62 24796.25 25097.71 23799.04 19294.66 25399.16 4296.92 30497.23 19697.87 21499.10 10986.11 29599.65 25991.65 30199.21 22898.82 250
IterMVS-LS98.55 11398.70 7498.09 21799.48 9794.73 25097.22 22299.39 10098.97 7899.38 6299.31 7496.00 18799.93 2698.58 6899.97 2399.60 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet97.69 18597.35 20198.69 15198.73 24697.02 17996.92 24098.75 25095.89 24798.59 17598.67 18892.08 27199.74 21496.72 16099.81 8999.32 176
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref99.77 105
IterMVS97.73 18398.11 14896.57 28399.24 13890.28 32295.52 31199.21 16098.86 8599.33 7299.33 7293.11 25799.94 2098.49 7499.94 3399.48 117
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon97.33 21096.92 21698.57 16999.09 17897.99 11596.79 24699.35 11793.18 29797.71 23598.07 25295.00 21999.31 32593.97 25899.13 24398.42 278
MVS_111021_LR98.30 14098.12 14798.83 13299.16 16798.03 11396.09 28399.30 13897.58 15898.10 20198.24 23798.25 4899.34 32196.69 16499.65 15499.12 218
DP-MVS98.93 5798.81 5899.28 7199.21 15098.45 8698.46 10999.33 12699.63 1299.48 4699.15 10297.23 12099.75 20597.17 13399.66 15399.63 44
ACMMP++99.68 143
HQP-MVS97.00 23296.49 24298.55 17498.67 26096.79 18596.29 27499.04 20396.05 24295.55 32096.84 29993.84 24799.54 28992.82 28699.26 22399.32 176
QAPM97.31 21196.81 22398.82 13398.80 24197.49 15699.06 5399.19 17090.22 32997.69 23799.16 9896.91 13899.90 4790.89 31899.41 20299.07 221
Vis-MVSNetpermissive99.34 2699.36 2199.27 7499.73 2898.26 9499.17 4199.78 599.11 6199.27 8299.48 5098.82 2299.95 1398.94 5299.93 3999.59 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet94.32 29795.62 26090.42 33998.46 28175.36 35696.29 27489.13 35495.25 26395.38 32699.75 792.88 26299.19 33394.07 25799.39 20496.72 331
IS-MVSNet98.19 15397.90 16799.08 9699.57 6297.97 12099.31 2098.32 27099.01 7498.98 12699.03 12891.59 27299.79 17495.49 22699.80 9399.48 117
HyFIR lowres test97.19 22196.60 23798.96 11599.62 5497.28 16595.17 31999.50 6594.21 28799.01 12198.32 23286.61 29199.99 297.10 14199.84 7399.60 52
EPMVS93.72 31093.27 31095.09 31696.04 34987.76 33098.13 12885.01 35694.69 27496.92 27898.64 19578.47 33999.31 32595.04 22996.46 33398.20 284
PAPM_NR96.82 24096.32 24798.30 20699.07 18296.69 19297.48 20598.76 24795.81 24896.61 29396.47 30794.12 24599.17 33490.82 32097.78 31399.06 222
TAMVS98.24 15098.05 15698.80 13599.07 18297.18 17197.88 16298.81 24296.66 22099.17 10199.21 8794.81 22799.77 19496.96 14599.88 6499.44 135
PAPR95.29 27294.47 28097.75 23597.50 32695.14 24494.89 32598.71 25591.39 32195.35 32795.48 32794.57 23499.14 33784.95 33997.37 31998.97 234
RPSCF98.62 10398.36 12399.42 5199.65 4799.42 598.55 8999.57 4397.72 14998.90 13899.26 7996.12 18299.52 29595.72 21799.71 12899.32 176
Vis-MVSNet (Re-imp)97.46 20397.16 20898.34 20299.55 7396.10 21498.94 6498.44 26698.32 11498.16 19798.62 20188.76 28599.73 21993.88 26299.79 9799.18 209
test_040298.76 7498.71 7198.93 11999.56 6998.14 10398.45 11099.34 12199.28 4498.95 13198.91 14898.34 4699.79 17495.63 22199.91 5498.86 246
MVS_111021_HR98.25 14898.08 15498.75 14599.09 17897.46 15895.97 28699.27 14797.60 15797.99 20898.25 23698.15 5999.38 31896.87 15099.57 17499.42 143
CSCG98.68 9098.50 9999.20 8199.45 10698.63 6998.56 8799.57 4397.87 14298.85 14698.04 25397.66 8499.84 10396.72 16099.81 8999.13 217
PatchMatch-RL97.24 21896.78 22498.61 16299.03 19597.83 13396.36 27199.06 19693.49 29697.36 26597.78 26495.75 19999.49 30293.44 27598.77 26598.52 272
API-MVS97.04 23196.91 21897.42 25497.88 31198.23 9998.18 12498.50 26497.57 16097.39 26296.75 30196.77 15199.15 33690.16 32299.02 25294.88 348
Test By Simon96.52 166
TDRefinement99.42 1999.38 1999.55 2099.76 2699.33 1199.68 599.71 1299.38 3599.53 3799.61 3098.64 2999.80 15498.24 8599.84 7399.52 97
USDC97.41 20797.40 19597.44 25398.94 20993.67 28495.17 31999.53 5994.03 28998.97 12899.10 10995.29 21299.34 32195.84 21399.73 11999.30 183
EPP-MVSNet98.30 14098.04 15799.07 9799.56 6997.83 13399.29 2598.07 27899.03 7298.59 17599.13 10592.16 26999.90 4796.87 15099.68 14399.49 111
PMMVS96.51 25095.98 25298.09 21797.53 32295.84 22594.92 32498.84 23691.58 31796.05 31095.58 32095.68 20199.66 25495.59 22398.09 30498.76 259
PAPM91.88 32490.34 32696.51 28498.06 30392.56 29492.44 34697.17 29586.35 34390.38 35196.01 31286.61 29199.21 33270.65 35495.43 34097.75 302
ACMMPcopyleft98.75 7598.50 9999.52 3899.56 6999.16 2998.87 6999.37 10797.16 20098.82 15299.01 13197.71 8399.87 7296.29 19099.69 13899.54 86
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CNLPA97.17 22296.71 22998.55 17498.56 27398.05 11296.33 27298.93 22196.91 20897.06 27397.39 28794.38 23899.45 31091.66 30099.18 23598.14 286
PatchmatchNetpermissive95.58 26695.67 25995.30 31497.34 33087.32 33297.65 18596.65 31095.30 26297.07 27298.69 18484.77 30499.75 20594.97 23298.64 27498.83 248
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS98.29 14397.95 16199.34 6598.44 28399.16 2998.12 13099.38 10396.01 24598.06 20498.43 22297.80 8099.67 24695.69 21999.58 17099.20 203
F-COLMAP97.30 21296.68 23199.14 8899.19 16098.39 8997.27 21699.30 13892.93 29996.62 29298.00 25495.73 20099.68 24092.62 29198.46 28499.35 169
ANet_high99.57 999.67 599.28 7199.89 798.09 10599.14 4499.93 199.82 299.93 299.81 499.17 1499.94 2099.31 30100.00 199.82 10
PNet_i23d91.80 32592.35 31790.14 34098.65 26673.10 35989.22 35299.02 20995.23 26597.87 21497.82 26378.45 34098.89 34588.73 32686.14 35398.42 278
wuyk23d96.06 25997.62 18491.38 33898.65 26698.57 7698.85 7296.95 30296.86 21099.90 599.16 9899.18 1298.40 34989.23 32599.77 10577.18 354
OMC-MVS97.88 17397.49 18999.04 10598.89 22398.63 6996.94 23799.25 15395.02 26698.53 18298.51 21597.27 11399.47 30693.50 27499.51 19199.01 228
MG-MVS96.77 24296.61 23697.26 25998.31 29193.06 29095.93 29498.12 27796.45 22797.92 20998.73 17993.77 25299.39 31691.19 31499.04 25199.33 175
wuykxyi23d99.36 2599.31 2899.50 4299.81 2198.67 6898.08 13499.75 898.03 12699.90 599.60 3499.18 1299.94 2099.46 2599.98 1999.89 3
AdaColmapbinary97.14 22496.71 22998.46 18898.34 28997.80 13996.95 23698.93 22195.58 25796.92 27897.66 27095.87 19799.53 29190.97 31599.14 24098.04 289
uanet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
ITE_SJBPF98.87 12799.22 14498.48 8499.35 11797.50 16698.28 19598.60 20497.64 8899.35 32093.86 26399.27 22198.79 255
DeepMVS_CXcopyleft93.44 33498.24 29494.21 26794.34 32964.28 35391.34 34894.87 34289.45 28392.77 35677.54 35393.14 34993.35 351
TinyColmap97.89 17197.98 15997.60 24498.86 22694.35 26496.21 27899.44 8897.45 17699.06 11098.88 15797.99 6999.28 33094.38 25099.58 17099.18 209
MAR-MVS96.47 25395.70 25798.79 13697.92 30899.12 4098.28 11798.60 26192.16 31195.54 32396.17 31194.77 23199.52 29589.62 32498.23 28897.72 304
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
LF4IMVS97.90 17097.69 17698.52 17999.17 16597.66 14897.19 22699.47 8096.31 23297.85 21798.20 24196.71 15699.52 29594.62 23999.72 12498.38 280
MSDG97.71 18497.52 18898.28 20898.91 21896.82 18494.42 33299.37 10797.65 15298.37 19398.29 23497.40 10599.33 32394.09 25699.22 22698.68 268
LS3D98.63 9898.38 12199.36 5797.25 33299.38 699.12 4899.32 12999.21 4798.44 18698.88 15797.31 10999.80 15496.58 17099.34 21098.92 239
CLD-MVS97.49 19997.16 20898.48 18699.07 18297.03 17794.71 32899.21 16094.46 27898.06 20497.16 29497.57 9099.48 30594.46 24399.78 10198.95 235
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS93.44 31392.23 31897.08 26299.25 13797.86 13195.61 30797.16 29692.90 30093.76 34398.65 19275.94 35095.66 35379.30 35297.49 31697.73 303
Gipumacopyleft99.03 4599.16 4198.64 15599.94 398.51 8299.32 1799.75 899.58 2198.60 17499.62 2898.22 5299.51 30097.70 11299.73 11997.89 292
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015